Smart Structures and Systems

Volume 36, Number 1, 2025, pages 51-70

DOI: 10.12989/sss.2025.36.1.051

A ground motion synthesis method based on Kernel Principal Component Analysis and genetic algorithm for accurate seismic analysis

Zhen Liu and Xingliang Ma

Abstract

Efficient and accurate ground motion simulation is key to achieving reliable structural seismic analysis. However, ground motions are significantly influenced by multiple factors, such as the source mechanism, propagation path, and site conditions, resulting in notable nonstationarity and spatial variability. Traditional ground motion synthesis methods based on statistical models are often inadequate to address these complexities. Therefore, this paper proposes a ground motion synthesis method based on Kernel Principal Component Analysis (KPCA) and Genetic Algorithm (GA). By extracting characteristic mother waves from specific earthquake records and using genetic algorithms, artificial ground motions that meet the target response spectrum and peak ground acceleration (PGA) are generated. The method is applied to the Hualien earthquake in Taiwan as an example, and the results show that the synthesized ground motions effectively match the target response spectrum and PGA, with a maximum error within 7%. Further power spectral analysis demonstrates a high similarity between the synthesized and natural ground motions in terms of power spectral characteristics. Moreover, a finite element analysis of a typical frame structure under both artificial and similar natural ground motions from a database shows consistent seismic responses and patterns between the two. To further validate the applicability of the proposed method, ten ground motions were removed from the database, and artificial ground motions were synthesized based on their acceleration response spectra and peak ground velocity (PGV) information. Comparisons of waveform characteristics, PGA, PGV, and acceleration response spectra indicate that the artificial ground motions effectively retain the waveform characteristics of natural ground motions. The proposed method provides an efficient tool for engineering seismic applications, capable of synthesizing artificial ground motions that preserve the waveform and damage characteristics of natural ground motions while meeting specified target response spectrum, PGV, PGA, and other parameters.

Key Words

genetic algorithm; ground motion synthesis; Kernel Principal Component Analysis (KPCA); nonstationarity; response spectrum; seismic simulation

Address

(1) Zhen Liu: School of Management Science and Engineering, Shandong Technology and Business University, No. 191, Binhai Middle Road, Laishan District, Yantai City, Shandong, China; (2) Xingliang Ma: School of Civil Engineering and Architecture, Changzhou Institute of Technology,